Paper Abstract and Keywords |
Presentation |
2017-11-10 13:00
Compressed Sensing CT image reconstruction using Bayesian Optimization for mixing multiple image priors Tomonori Suga, Masato Inoue (Waseda Univ.) IBISML2017-73 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In order to reduce the amount of radiation exposure, which increases the risk of cancer, many researches have been done to reconstruct CT images from sparse-view data by using Compressed Sensing techniques. The new model which uses sparsity of wavelet transform and Total Variation as image priors may be superior to other conventional models which use just one image prior, and most of them are optimized by ART method. However, the way of combining these image priors is difficult and not clear. In this study, we propose the method utilizing Bayesian Optimization for mixing these multiple image priors. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Compressed Sensing / Sparse Modeling / Bayesian Optimization / CT image reconstruction / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 293, IBISML2017-73, pp. 283-288, Nov. 2017. |
Paper # |
IBISML2017-73 |
Date of Issue |
2017-11-02 (IBISML) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
Download PDF |
IBISML2017-73 |
Conference Information |
Committee |
IBISML |
Conference Date |
2017-11-08 - 2017-11-10 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Univ. of Tokyo |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Information-Based Induction Science Workshop (IBIS2017) |
Paper Information |
Registration To |
IBISML |
Conference Code |
2017-11-IBISML |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Compressed Sensing CT image reconstruction using Bayesian Optimization for mixing multiple image priors |
Sub Title (in English) |
|
Keyword(1) |
Compressed Sensing |
Keyword(2) |
Sparse Modeling |
Keyword(3) |
Bayesian Optimization |
Keyword(4) |
CT image reconstruction |
Keyword(5) |
|
Keyword(6) |
|
Keyword(7) |
|
Keyword(8) |
|
1st Author's Name |
Tomonori Suga |
1st Author's Affiliation |
Waseda University (Waseda Univ.) |
2nd Author's Name |
Masato Inoue |
2nd Author's Affiliation |
Waseda University (Waseda Univ.) |
3rd Author's Name |
|
3rd Author's Affiliation |
() |
4th Author's Name |
|
4th Author's Affiliation |
() |
5th Author's Name |
|
5th Author's Affiliation |
() |
6th Author's Name |
|
6th Author's Affiliation |
() |
7th Author's Name |
|
7th Author's Affiliation |
() |
8th Author's Name |
|
8th Author's Affiliation |
() |
9th Author's Name |
|
9th Author's Affiliation |
() |
10th Author's Name |
|
10th Author's Affiliation |
() |
11th Author's Name |
|
11th Author's Affiliation |
() |
12th Author's Name |
|
12th Author's Affiliation |
() |
13th Author's Name |
|
13th Author's Affiliation |
() |
14th Author's Name |
|
14th Author's Affiliation |
() |
15th Author's Name |
|
15th Author's Affiliation |
() |
16th Author's Name |
|
16th Author's Affiliation |
() |
17th Author's Name |
|
17th Author's Affiliation |
() |
18th Author's Name |
|
18th Author's Affiliation |
() |
19th Author's Name |
|
19th Author's Affiliation |
() |
20th Author's Name |
|
20th Author's Affiliation |
() |
Speaker |
Author-1 |
Date Time |
2017-11-10 13:00:00 |
Presentation Time |
150 minutes |
Registration for |
IBISML |
Paper # |
IBISML2017-73 |
Volume (vol) |
vol.117 |
Number (no) |
no.293 |
Page |
pp.283-288 |
#Pages |
6 |
Date of Issue |
2017-11-02 (IBISML) |
|